8 ms·

Are you a stream of words or are your words the “simplistic” projection of your abstract thoughts? I don’t at all discount the importance of language in so many

• akoboldfrying 10mo ago
  LLMs and human brains are both just mechanisms. Why would one mechanism a priori be capable of "learning abstract thought", but no others? If it turns out that LLMs don't model human brains well enough to qualify as "learning abstract thought" the way humans do, some future technology will do so. Human brains aren't magic, special or different.
  • meheleventyone 10mo ago
    Human brains aren’t magic in the literal sense but do have a lot of mechanisms we don’t understand. They’re certainly special both within the individual but also as a species on this planet. There are many similar to human brains but none we know of with similar capabilities. They’re also most obviously certainly different to LLMs both in how they work foundationally and in capability. I definitely agree with the materialist view that we will ultimately be able to emulate the brain using computation but we’re nowhere near that yet nor should we undersell the complexity involved.
    • panarky 10mo ago
      When someone says "AIs aren't really thinking" because AIs don't think like people do, what I hear is "Airplanes aren't really flying" because airplanes don't fly like birds do.
      • meheleventyone 10mo ago
        This really shows how imprecise a term 'thinking' is here. In this sense any predictive probabilistic blackbox model could be termed 'thinking'. Particularly when juxtaposed against something as concrete as flight that we have modelled extremely accurately.
        • lostmsu 10mo ago
          Yes, to a degree. A very low degree at that.
          • atomicthumbs 10mo ago
            AIs think like a rock flies.
      • nkrisc 10mo ago
        If I shake some dice in a cup are they thinking about what number they’ll reveal when I throw them?
        • shawabawa3 10mo ago
          that depends, if you explain the rules of the game you're playing and give the dice a goal to win the game, do they adjust the numbers they reveal according to the rules of the game? If so, yes, they're thinking
          • brendoelfrendo 10mo ago
            As someone who plays a lot of Dungeons and Dragons, it sure feels like the dice are thinking sometimes.
          • nkrisc 10mo ago
            The rules of the game are to reveal two independent numbers in the range [1,6].
        • danielbln 10mo ago
          If I take a plane apart and throw all the parts off a cliff, will they achieve sustained flight? If I throw some braincells into a cup alongside the dice, will they think about the outcome anymore than the dice alone?
        • kortex 10mo ago
          https://en.wikipedia.org/wiki/Emergence https://en.wikipedia.org/wiki/Emergence
      • jibal 10mo ago
        That's a fallacy of denial of the antecedent. You are inferring from the fact that airplanes really fly that AIs really think, but it's not a logically valid inference.
        • hackernewds 10mo ago
          Yeah at that point, just arguing semantics
        • fc417fc802 10mo ago
          Observing a common (potential) failure mode is not equivalent to asserting a logical inference. It is only a fallacy if you "P, therefore C" which GP is not (at least to my eye) doing.
        • jibal 10mo ago
          "Observing a common (potential) failure mode" That's not what we have here. "It is only a fallacy if you "P, therefore C" which GP is not (at least to my eye) doing." Some people are willfully blind.
      • staticman2 10mo ago
        Whenever someone paraphrases a folksy aphorism about airplanes and birds or fish and submarines I suppose I'm meant to rebut with folksy aphorisms like: "A.I. and humans are as different as chalk and cheese." As aphorisms are a good way to think about this topic?
    • Davidzheng 10mo ago
      ofc, and probably will never understand because of sheer complexity. It doesn't mean we can't replicate the output distribution through data. Probably when we do in efficient manners, the mechanisms (if they are efficient) will be learned too.
    • DoctorOetker 10mo ago
      I agree we shouldn't undersell or underestimate the complexity involved, but when LLM's start contributing significant ideas to scientists and mathematicians, its time to recognize that whatever tricks are used in biology (humans, octopuses, ...) may still be of interest and of value, but they no longer seem like the unique magical missing ingredients which were so long sought after. From this point on its all about efficiencies: modeling efficiency: how do we best fit the elephant, with bezier curves, rational polynomials, ...? memory bandwidth training efficiency: when building coincidence statistics, say bigrams, is it really necessary to update the weights for all concepts? a co-occurence of 2 concepts should just increase the predicted probability for the just observed bigram and then decrease a global coefficient used to scale the predicted probabilities. I.e. observing a baobab tree + an elephant in the same image/sentence/... should not change the relative probabilities of observing french fries + milkshake versus bicycle + windmill. This indicates different architectures should be possible with much lower training costs, by only updating weights of the concepts observed in the last bigram. and so on with all other kinds of efficiencies.
  • jpkw 10mo ago
    Right, I'm just going to teach my dog to do my job then and get free money as my brain is no more magic, special or different to theirs!
  • littlestymaar 10mo ago
    > LLMs and human brains are both just mechanisms. Why would one mechanism a priori be capable of "learning abstract thought", but no others? “Internal combustion engines and human brains are both just mechanisms. Why would one mechanism a priori be capable of "learning abstract thought", but no others?” The question isn't about what an hypothetical mechanism can do or not, it's about whether the concrete mechanism we built does or not. And this one doesn't.
    • ben_w 10mo ago
      The general argument you make is correct, but you conclusion "And this one doesn't." is as yet uncertain. I will absolutely say that all ML methods known are literally too stupid to live, as in no living thing can get away with making so many mistakes before it's learned anything, but that's the rate of change of performance with respect to examples rather than what it learns by the time training is finished. What is "abstract thought"? Is that even the same between any two humans who use that word to describe their own inner processes? Because "imagination"/"visualise" certainly isn't.
      • rob74 10mo ago
        > no living thing can get away with making so many mistakes before it's learned anything If you consider that LLMs have already "learned" more than any one human in this world is able to learn, and still make those mistakes, that suggests there may be something wrong with this approach...
        • quantummagic 10mo ago
          But humans do the same thing. How many eons did we make the mistake of attributing everything to God's will, without a scientific thought in our heads? It's really easy to be wrong, when the consequences don't lead to your death, or are actually beneficial. The thinking machines are still babies, whose ideas aren't honed by personal experience; but that will come, in one form or another.
          • 10mo ago
  • RayVR 10mo ago
    I'm not arguing that human brains are magic. the current AI models will probably teach us more about what we didn't know about intelligence than anything else.
  • thesz 10mo ago
    > Human brains aren't magic, special or different. DNA inside neurons uses superconductive quantum computations [1]. [1] https://www.nature.com/articles/s41598-024-62539-5 https://www.nature.com/articles/s41598-024-62539-5 As the result, all living cells with DNA emit coherent (as in lasers) light [2]. There is a theory that this light also facilitates intercellular communication. [2] https://www.sciencealert.com/we-emit-a-visible-light-that-vanishes-when-we-die-says-surprising-new-study https://www.sciencealert.com/we-emit-a-visible-light-that-va... Chemical structures in dendrites, not even neurons, are capable to compute XOR [3] which require multilevel artificial neural network with at least 9 parameters. Some neurons in brain have hundredths of thousands of dendrites, we are now talking of millions of parameters only in single neuron's dendrites functionality. [3] https://www.science.org/doi/10.1126/science.aax6239 https://www.science.org/doi/10.1126/science.aax6239 So, while human brains aren't magic, special or different, they are just extremely complex. Imagine building a computer with 85 billions of superconducting quantum computers, optically and electrically connected, each capable of performing computations of a non-negligibly complex artificial neural network.
    • danielbln 10mo ago
      They are extremely complex, but is that complexity required for building a thinking machine? We don't understand bird physiology enough to build a bird from scratch, but an airplane flies just the same.
      • sublinear 10mo ago
        Are we not just getting lost in semantics when we say "fly"? An airplane does not at all perform the same behavior as a bird. Do we say that boats or submarines "swim"? Planes and boats disrupt the environments they move through and air and sea freight are massive contributors to pollution.
        • IAmBroom 10mo ago
          You seem to have really gone off the rails midway through that post...
  • arowthway 10mo ago
    For some unexplainable reason your subjective experience happens to be localized in your brain. Sounds pretty special to me.
    • mapontosevenths 10mo ago
      There is nothing special about that either. LLM's also have self awareness/introspection, or at least a some version of it. https://www.anthropic.com/research/introspection https://www.anthropic.com/research/introspection Its hard to tell sometimes because we specifically train them to believe they don't.
      • arowthway 10mo ago
        Thanks for the link, I haven't seen this before and it's interesting. I don't think the version of self awareness they demonstrated is synonymous with subjective experience. But same thing can be said about any human other then me. Damn, just let me believe all brains are magical or I'll fall into solipsism.
  • nephihaha 10mo ago
    There isn't anything else around quite like a human brain that we know of, so yes, I'd say they're special and different. Animals and computers come close in some ways but aren't quite there.
  • d-lisp 10mo ago
    (Motors and human brains are both just mechanisms, the reason one is a priori capable of learning abstract thought and not the other ?) While I agree to some extent with the materialistic conception, the brain is not an isolated mechanism, but rather the element of a system which itself isn't isolated from the experience of being a body in a world interacting with different systems to form super systems. The brain must be a very efficient mechanism, because it doesn't need to ingest the whole textual production of the human world in order to know how to write masterpieces (music, litterature, films, software, theorems etc...). Instead the brain learns to be this very efficient mechanism with (as a starting process) feeling its own body sh*t on itself during a long part of its childhood. I can teach someone to become really good at producing fine and efficient software, but on the contrary I can only observe everyday that my LLM of choice keeps being stupid even when I explain it how it fails. ("You're perfectly right !"). It is true that there's nothing magical about the brain, but I am pretty sure it must be stronger tech than a probabilistic/statistical next word guesser (otherwise there would be much more consensus about the usability of LLMs I think).
    • cindyllm 10mo ago
      [dead]
  • jibal 10mo ago
    Thermometers and human brains are both mechanisms. Why would one be capable of measuring temperature and other capable of learning abstract thought? > If it turns out that LLMs don't model human brains well enough to qualify as "learning abstract thought" the way humans do, some future technology will do so. Human brains aren't magic, special or different. Google "strawman".
• Davidzheng 10mo ago
  Even if they are "simplistic projections", which I don't think is the correct way to think about it, there's no reason that more LLM thoughts in middle layers can't also exist and project down at the end. Though there might be efficency issues because the latent thoughts have to be recomputed a lot. Though I do think in human brains it's also an interplay where what we write/say also loops back into the thinking as well. Which is something which is efficient for LLMs.
• ACCount37 10mo ago
  Words are the "simplistic" projection of an LLM's abstract thoughts. An LLM has: words in its input plane, words in its output plane, and A LOT of cross-linked internals between the two. Those internals aren't "words" at all - and it's where most of the "action" happens. It's how LLMs can do things like translate from language to language, or recall knowledge they only encountered in English in the training data while speaking German.
  • Hendrikto 10mo ago
    > It's how LLMs can do things like translate from language to language The heavy lifting here is done by embeddings. This does not require a world model or “thought”.
    • traverseda 10mo ago
      LLMs are compression and prediction. The most efficient way to (lossfully) compress most things is by actually understanding them. Not saying LLMs are doing a good job of that, but that is the fundamental mechanism here.
      • emp17344 10mo ago
        Where’s the proof that efficient compression results in “understanding”? Is there a rigorous model or theorem, or did you just make this up?
        • traverseda 10mo ago
          No answer I give will be satisfying to you until I could come up with a rigorous mathematical definition of understanding, which is de-facto solving the hard AI problem. So there's not really point in talking about it is there? If you're interested in why compression is like understanding in many ways, I'd suggest reading through the wikipedia article on Kolmogorov complexity. https://en.wikipedia.org/wiki/Kolmogorov_complexity https://en.wikipedia.org/wiki/Kolmogorov_complexity
        • 10mo ago
• balamatom 10mo ago
  I'm definitely a stream of words. My "abstract thoughts" are a stream of words too, they just don't get sounded out. Tbf I'd rather they weren't there in the first place. But bodies which refuse to harbor an "interiority" are fast-tracked to destruction because they can't suf^W^W^W be productive. Funny movie scene from somewhere. The sergeant is drilling the troops: "You, private! What do you live for!", and expects an answer along the lines of dying for one's nation or some shit. Instead, the soldier replies: "Well, to see what happens next!"
  • A4ET8a8uTh0_v2 10mo ago
    << My "abstract thoughts" are a stream of words too, they just don't get sounded out. Hmm, seems unlikely. They are not sounded out part is true, sure, but I question whether 'abstract thoughts' can be so easily dismissed as mere words. edit: come to think of it and I am asking this for a reason: do you hear your abstract thoughts?
    • carb 10mo ago
      Different people have different levels of internal monologuing or none at all. I don't generally think with words in sentences in my head, but many people I know do.
      • A4ET8a8uTh0_v2 10mo ago
        Hmm, yes, but, and it is not a small but, do people -- including full blown internal monologue people - think thoughts akin to: move.panic.fear.run that effectively becomes one thought and not a word exactly. I am stating it like this, because I worry that my initial point may have been lost. edit: I can only really speak for myself, but I am curious how people might respond to the distinction.
      • jibal 10mo ago
        Internal monologue is a like a war correspondent's report of the daily battle. The journalist didn't plan or fight the battle, they just provided an after-the-fact description. Likewise the brain's thinking--a highly parallelized process involving billions of neurons--is not done with words. Play a little game of "what word will I think of next?" ... just let it happen. Those word choices are fed to the monologue, they aren't a product of it.
• gardenhedge 10mo ago
  I am a stream of words - I have even ran out of tokens while speaking before :) But raising kids, I can clearly see that intelligence isn't just solved by LLMs
  • lostmsu 10mo ago
    > But raising kids, I can clearly see that intelligence isn't just solved by LLMs Funny, I have the opposite experience. Like early LLMs kids tend to give specific answers to the questions they don't understand or don't really know or remember the answer to. Kids also loop (give the same reply repeatedly to different prompts), enter highly emotional states where their output is garbled (everyone loves that one), etc. And it seems impossible to correct these until they just get smarter as their brain grows. What's even more funny is that adults tend to do all these things as well, just less often.
    • fc417fc802 10mo ago
      Same failure modes, but not a general solution to intelligence.
      • lostmsu 10mo ago
        What makes you think so?
        • fc417fc802 10mo ago
          The lack of results so far. The observable behavior exhibits many uncanny similarities but also clearly has missing pieces. As the person you initially responded to said, observing children growing up should make it obvious. Or if we shift to stating the obvious, there's the minor detail that the vast majority of architectures lack the ability to learn during inference. That's one of the basic things that biological systems are capable of.